Nutritional management adherence via an ePRO platform in patients with cancer: a machine learning model study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Electronic patient-reported outcome (ePRO) systems have significant potential for providing individualized and continuous nutritional management for patients with cancer. However, adherence to ePRO-guided nutritional interventions varies significantly, and the key factors associated with adherence remain poorly understood. This study aimed to assess adherence to nutritional targets via ePRO platforms and identify predictors influencing adherence to optimize management strategies. Methods: This multicenter, prospective longitudinal cohort study included 8268 patients with cancer from March 2021 to April 2024 (registration number: ChiCTR2100047535). Adherence was defined as the ratio of actual to prescribed intake for both total energy (TEI) and total protein (TPI). Adherence to TEI and TPI targets was monitored throughout the study period based on prescriptions generated by ePRO-guided nutritional management. The proportion of actual/prescribed intake <60% was set as low adherence. Explainable machine learning models were used to identify predictive features, with SHapley Additive exPlanation (SHAP) analysis ranking variable importance. Two-way fixed-effect logistic regression models were applied to further assess longitudinal predictors of adherence. Findings: Among 8268 patients (median age, 61 years; 61.9% male, 38.1% female), 2727 (33.0%) and 3332 (40.3%) failed to meet TEI and TPI targets, respectively. The LightGBM model achieved superior predictive performance (area under the receiver operating characteristic curve: TEI = 0.861, TPI = 0.821). Key predictors of lower adherence to both TEI and TPI included advanced TNM stage (TEI: odds ratio [OR] = 1.18, 95% CI: 1.11-1.26; TPI: OR = 1.39, 95% CI: 1.27-1.53), poorer Eastern Cooperative Oncology Group performance status (TEI: OR = 1.18, 95% CI: 1.11-1.26; TPI: OR = 1.39, 95% CI: 1.27-1.53), higher Patient-Generated Subjective Global Assessment scores (TEI: OR = 1.08, 95% CI: 1.08-1.09; TPI: OR = 1.08, 95% CI: 1.07-1.10), elevated platelet counts (TEI: OR = 1.01, 95% CI: 1.00-1.01; TPI: OR = 1.01, 95% CI: 1.00-1.01), walking time <60 min/day (TEI: OR = 2.42, 95% CI: 2.18-2.69; TPI: OR = 2.59, 95% CI: 2.19-3.06), sleep duration <8 h/day (TEI: OR = 1.48, 95% CI: 1.25-1.76; TPI: OR = 1.41, 95% CI: 1.29-1.52), and nausea (TEI: OR = 1.32, 95% CI: 1.23-1.41; TPI: OR = 1.44, 95% CI: 1.37-1.51). Conversely, factors associated with higher adherence included female sex and higher levels of serum albumin, alanine transaminase, and glucose. Interpretation: In this large multicenter study, over one-third of patients failed to meet ePRO-guided nutritional targets, highlighting substantial challenges in adherence. Further, we identified key predictors associated with low adherence to ePRO-guided nutritional management in patients with cancer, which might help identify at-risk patients and guide future research. Funding: Wu Jieping Medical Foundation (320.6750.2021-02-22).
Source: EClinicalMedicine
Authors: Si-Wei Xie, Jia-Xin Huang, Hui-Min Qu, Zhi-Gang Feng, Xin-Yi Wang, Zhen-Guang Du, Ming-Hui Zhang, Shu-Qing Wei, Jun Li, Li-Li Hong, Li-Li Wang, Jing-Hui Bai, Kai-Feng Wang, Xue-Bang Zhang, Xian Shen, Xiao-Dong Chen, Le Tian, Xi Zhang, Min Yang, Ning Li, Meng Tang, Chen-Xin Song, Bao-Hua Zou, Sheng-Ling Qin, Rong Qin, Ming-Hua Cong
Institutions: Johns Hopkins University, Chinese Academy of Medical Sciences & Peking Union Medical College, Cancer Hospital of Chinese Academy of Medical Sciences, Liaoning Provincial People's Hospital, Chifeng Municipal Hospital, Shanxi Medical University, Shanxi Provincial Cancer Hospital, Second Hospital of Tianjin Medical University, Liaoning Cancer Hospital & Institute, Shanghai Jiao Tong University, Renji Hospital, Shanghai Cancer Institute, State Key Laboratory of Oncogene and Related Genes, First Affiliated Hospital of Wenzhou Medical University
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $5,780
Funder: Wu Jieping Medical Foundation
Award: G2071695408
OpenAlex ID: W4411951152
